Publicação:
A malware detection system inspired on the human immune system

dc.contributor.authorDe Oliveira, Isabela Liane [UNESP]
dc.contributor.authorGrégio, André Ricardo Abed
dc.contributor.authorCansian, Adriano Mauro [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionRenato Archer IT Research Center (CTI/MCT)
dc.date.accessioned2014-05-27T11:26:53Z
dc.date.available2014-05-27T11:26:53Z
dc.date.issued2012-07-23
dc.description.abstractMalicious programs (malware) can cause severe damage on computer systems and data. The mechanism that the human immune system uses to detect and protect from organisms that threaten the human body is efficient and can be adapted to detect malware attacks. In this paper we propose a system to perform malware distributed collection, analysis and detection, this last inspired by the human immune system. After collecting malware samples from Internet, they are dynamically analyzed so as to provide execution traces at the operating system level and network flows that are used to create a behavioral model and to generate a detection signature. Those signatures serve as input to a malware detector, acting as the antibodies in the antigen detection process. This allows us to understand the malware attack and aids in the infection removal procedures. © 2012 Springer-Verlag.en
dc.description.affiliationSão Paulo State University (Unesp), São José do Rio Preto, SP
dc.description.affiliationRenato Archer IT Research Center (CTI/MCT), Campinas, SP
dc.description.affiliationUnespSão Paulo State University (Unesp), São José do Rio Preto, SP
dc.format.extent286-301
dc.identifierhttp://dx.doi.org/10.1007/978-3-642-31128-4_21
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), v. 7336 LNCS, n. PART 4, p. 286-301, 2012.
dc.identifier.doi10.1007/978-3-642-31128-4_21
dc.identifier.issn0302-9743
dc.identifier.issn1611-3349
dc.identifier.lattes0095921943345974
dc.identifier.orcid0000-0003-4494-1454
dc.identifier.scopus2-s2.0-84863940774
dc.identifier.urihttp://hdl.handle.net/11449/73443
dc.identifier.wosWOS:000308289700021
dc.language.isoeng
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.relation.ispartofsjr0,295
dc.rights.accessRightsAcesso aberto
dc.sourceScopus
dc.subjectdata mining
dc.subjecthuman immune system
dc.subjectmalicious code
dc.subjectAntigen detections
dc.subjectBehavioral model
dc.subjectExecution trace
dc.subjectHuman bodies
dc.subjectHuman immune systems
dc.subjectMalicious codes
dc.subjectMalware attacks
dc.subjectMalware detection
dc.subjectMalwares
dc.subjectNetwork flows
dc.subjectChemical detection
dc.subjectComputer aided network analysis
dc.subjectComputer crime
dc.subjectData mining
dc.subjectDetectors
dc.subjectNetwork security
dc.subjectImmunology
dc.titleA malware detection system inspired on the human immune systemen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.springer.com/open+access/authors+rights
dspace.entity.typePublication
unesp.author.lattes0095921943345974[3]
unesp.author.orcid0000-0003-4494-1454[3]
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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